• Journal of The Korean Association For Science Education
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• v.33 no.4
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• pp.735-750
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• 2013

The purpose of this study is to relieve the difficulties caused by science terminology in science learning and increasing the efficiency of science education. The reason why students experience difficulties in science terminology is because science words are used without being filtered by a criteria and students have not had the opportunity to be educated properly in science terminology. As a way to solve this problem, we propose establishing a criteria about the science words used in science education and to teach the science words systematically to the students under the criteria. In this study, we used the method of empirical linguistics that investigate the science terminologies actually used in science education to establish a criteria for science words. As a basic research for this, we analyzed all words contained in the physics section of science textbooks for elementary and secondary schools. And then, we collected all words used in the physics section of science textbook, and selected the science words for teaching, and rated them by grade. As a result, a total of 930 physics terms were selected as the science words for grade 3 to 10. The numbers of physics terms per grade were as follows: 66 words for the 3rd grade, 38 words for the 4th grade, 35 words for the 5th grade, 28 words for the 6th grade, 203 words for the 7th grade, 135 words for the 8th grade, 123 words for the 9th grade, and 302 words for the 10th grade.

• Journal of The Korean Association of Information Education
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• v.6 no.3
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• pp.328-337
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• 2002

Looking at multimedia education contents from a design point of view, the instructor's design model may differ from the child's understanding model due to gap of the instructor's and child's knowledge. This fact implies it impacts the effectiveness of the education contents. The learning efficiency of Korean typography in WBI for children depends on the font-family, line space, font-size, the age of user, the output device such as the monitor, and other various factors. In this paper, we measured and analyzed on readability of Korean typography in WBI for children by reading speed method. The results of experiments show that readability depends on the font-family of typography, age(grade), and sex of children. In detail, "Goolymche" has the shortest time to be read, and girl and the highest grade students of elementary school have shorter time than boy and the lower grade students. Moreover, we consider the elegance of typography in WBI for holding children's interests because they prefer "Yopseoche". We provide some CSSs in WBI for children based on the experimental results, to used in school fields.

• Journal of Advanced Navigation Technology
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• v.15 no.2
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• pp.287-297
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• 2011

As electronic mails are being widely used for facility and speedness of information communication, as the amount of spam mails which have malice and advertisement increase and cause lots of social and economic problem. A number of approaches have been proposed to alleviate the impact of spam. These approaches can be categorized into pre-acceptance and post-acceptance methods. Post-acceptance methods include bayesian filters, collaborative filtering and e-mail prioritization which are based on words or sentances. But, spammers are changing those characteristics and sending to avoid filtering system. In the case of Korean, the abnormal usages can be much more than other languages because syllable is composed of chosung, jungsung, and jongsung. Existing formal expressions and learning algorithms have the limits to meet with those changes promptly and efficiently. So, we present an methods for recognizing Korean abnormal language(Koral) to improve accuracy and efficiency of filtering system. The method is based on syllabic than word and Smith-waterman algorithm. Through the experiment on filter keyword and e-mail extracted from mail server, we confirmed that Koral is recognized exactly according to similarity level. The required time and space costs are within the permitted limit.

• Journal of KIISE
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• v.42 no.4
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• pp.496-503
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• 2015

Most programming languages are designed based on English. It becomes another barrier in learning programming languages in non-English speaking country. If a programming language is presented using a native language, the education cost of programming will be much cheaper and the programming itself can be much more fun. However, designing the programming languages based on native languages has not been much focused or published up to now. It is partly because the evolution of popular programming languages is so fast, and partly because the efficiency of programs is much stressed than the source code. But, the designing of programming languages based on native language is not a small issue, especially if we reflect on the education of programming. In fact, there have been significant efforts reported in the Korean programming languages so far, but it has not practically been used in the education. This paper introduces yet another Korean programming language, namely Sprout, which is concise and can be easily learned by beginners. To demonstrate the conciseness of Sprout, we have performed two experiments on Sprout. Firstly, we compared the sizes of the programs in Sprout with those in former Korean programming languages. Secondly, we compared the size of Sprout, the language itself, with those of popular programming languages such as C and Python. According to the experiments, Sprout programs are more concise to 10% on average than those in former Korean languages. Furthermore, Sprout itself is more compact to 24% on average than other popular programming languages.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.27-36
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• 2010

In Web registration pages and online polling applications, CAPTCHA(Completely Automated Public Turing Test To Tell Computers and Human Apart) is used for distinguishing human users from automated programs. Text-based CAPTCHAs have been widely used in many popular Web sites in which distorted text is used. However, because the advanced optical character recognition techniques can recognize the distorted texts, the reliability becomes low. Image-based CAPTCHAs have been proposed to improve the reliability of the text-based CAPTCHAs. However, these systems also are known as having some drawbacks. First, some image-based CAPTCHA systems with small number of image files in their image dictionary is not so reliable since attacker can recognize images by repeated executions of machine learning programs. Second, users may feel uncomfortable since they have to try CAPTCHA tests repeatedly when they fail to input a correct keyword. Third, some image-base CAPTCHAs require high communication cost since they should send several image files for one CAPTCHA. To solve these problems of image-based CAPTCHA, this paper proposes a new CAPTCHA based on both image and text. In this system, an image and keywords are integrated into one CAPTCHA image to give user a hint for the answer keyword. The proposed CAPTCHA can help users to input easily the answer keyword with the hint in the fused image. Also, the proposed system can reduce the communication costs since it uses only a fused image file for one CAPTCHA. To improve the reliability of the image-text fusion CAPTCHA, we also propose a dynamic building method of large image dictionary from gathering huge amount of images from theinternet with filtering phase for preserving the correctness of CAPTCHA images. In this paper, we proved that the proposed image-text fusion CAPTCHA provides users more convenience and high reliability than the image-based CAPTCHA through experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.546-554
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• 2019

Typically, closed-circuit television (CCTV) monitoring is mainly used for post-processes (i.e. to provide evidence after an incident has occurred), but by using a streaming video feed, machine-based learning, and advanced image recognition techniques, current technology can be extended to respond to crimes or reports of missing persons in real time. The multi-CCTV cooperation technique developed in this study is a program model that delivers similarity information about a suspect (or moving object) extracted via CCTV at one location and sent to a monitoring agent to track the selected suspect or object when he, she, or it moves out of range to another CCTV camera. To improve the operating efficiency of local government CCTV control centers, we describe here the partial automation of a CCTV control system that currently relies upon monitoring by human agents. We envisage an integrated crime prevention service, which incorporates the cooperative CCTV network suggested in this study and that can easily be experienced by citizens in ways such as determining a precise individual location in real time and providing a crime prevention service linked to smartphones and/or crime prevention/safety information.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.537-542
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• 2017

Aggressive driving is a major cause of car accidents. Previous studies have mainly analyzed young driver's aggressive driving tendency, yet they were only done through pure clustering or classification technique of machine learning. However, since elderly people have different driving habits due to their fragile physical conditions, it is necessary to develop a new method such as enhancing the characteristics of driving data to properly analyze aggressive driving of elderly drivers. In this study, acceleration data collected from a smartphone of a driving vehicle is analyzed by a newly proposed ECA(Enhanced Clustering method for Acceleration data) technique, coupled with a conventional clustering technique (K-means Clustering, Expectation-maximization algorithm). ECA selects high-intensity data among the data of the cluster group detected through K-means and EM in all of the subjects' data and models the characteristic data through the scaled value. Using this method, the aggressive driving data of all youth and elderly experiment participants were collected, unlike the pure clustering method. We further found that the K-means clustering has higher detection efficiency than EM method. Also, the results of K-means clustering demonstrate that a young driver has a driving strength 1.29 times higher than that of an elderly driver. In conclusion, the proposed method of our research is able to detect aggressive driving maneuvers from data of the elderly having low operating intensity. The proposed method is able to construct a customized safe driving system for the elderly driver. In the future, it will be possible to detect abnormal driving conditions and to use the collected data for early warning to drivers.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• Journal of Korean society of Dental Hygiene
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• v.11 no.5
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• pp.811-822
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• 2011

Objectives : The purpose of this study was to examine the relationship of the self-efficacy of dental hygiene students to their stressors and ways of stress-adaptation patterns. Methods : The subjects in this study were dental hygiene juniors in four selected colleges located in the metropolitan area. Results : 1. They got a mean of 3.22 in self-efficacy. They gave the highest mark(3.50) to an item 'I can attain it if I set a primary goal.' 2. They got a mean of 3.18 in stressors. Among the stressors, task assignments(3.74) were identified as the greatest stressor, followed by the curriculum(3.25), learning environments(3.16), prospects of employment (3.07) and test anxiety(2.95). 3. They got a mean of 2.02 in stress-adaptation method. They got 2.31 and 1.72 in long-term and short-term adaptation respectively, which showed that long-term stress adaptation method were more prevailing than short-term ones. 4. As a result of analyzing whether there would be any gaps in self-efficacy according to general characteristics, statistically significant gaps were found in that regard according to experience of preparing for college admission after leaving high school, academic standing, satisfaction with the department of dental hygiene and prospects of employment(p<.05). 5. As a result of checking the relationship of their self-efficacy to their stressors and ways of stress adaptation method, there were statistically significant differences in that aspect according to examinations and prospect of employment(p<0.05). As for ways of stress adaptation method, there were statistically significant differences in long-term adaptation method (p<0.05). Conclusions : As it's found that the level of the self-efficacy of the dental hygiene students was linked to the efficiency of their ways of stress adaptation method, the development and implementation of programs geared toward boosting the self-efficacy of dental hygiene students are required to teach them to successfully cope with various kinds of stress that they are likely to face after getting a job.

• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.114-125
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• 2020

Despite the various artificial neural networks that have been developed, most of the discharge models in previous studies have been developed using deep neural networks. This study aimed to develop a discharge model using a convolution neural network (CNN), which was used to solve classification problems. Furthermore, the applicability of CNN was evaluated. The photographs (pictures or images) for input data to CNN could not clearly show the characteristics of the study area as well as precipitation. Hence, the model employed in this study had to use numerical images. To solve the problem, the CN of NRCS was used to generate images as input data for the model. The generated images showed a good possibility of applicability as input data. Moreover, a new application of CN, which had been used only for discharge prediction, was proposed in this study. As a result of CNN training, the model was trained and generalized stably. Comparison between the actual and predicted values had an R² of 0.79, which was relatively high. The model showed good performance in terms of the Pearson correlation coefficient (0.84), the Nash-Sutcliffe efficiency (NSE) (0.63), and the root mean square error (24.54 ㎥/s).